Qwen 72B — Hardware Requirements & GPU Compatibility
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Qwen 72B is a 72.3B-parameter open language model from Alibaba in the Qwen family. It supports a context window of up to 32,768 tokens. At Q4_K_M it needs about 47.71 GB of VRAM — see which GPUs and Macs can run it below.
3.9M downloads
362 likesSpecifications
- Publisher
- Alibaba
- Family
- Qwen
- Parameters
- 72.3B
- Architecture
- QWenLMHeadModel
- Context Length
- 32,768 tokens
- Vocabulary Size
- 152,064
- Release Date
- 2023-11-26
- License
- Other
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HuggingFace
How Much VRAM Does Qwen 72B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 33.8 GB | — | 30.72 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 34.8 GB | — | 31.63 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 38.8 GB | — | 35.24 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 47.7 GB | — | 43.37 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 56.7 GB | — | 51.51 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 65.6 GB | — | 59.64 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 79.5 GB | — | 72.29 GB | 8-bit quantization, near-lossless |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Qwen 72B?
Q4_K_M · 47.7 GBQwen 72B (Q4_K_M) requires 47.7 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 63+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Qwen 72B?
Q4_K_M · 47.7 GB26 devices with unified memory can run Qwen 72B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (64 GB).
Runs great
— Plenty of headroom
Where to Download Qwen 72B
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
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Frequently Asked Questions
- How much VRAM does Qwen 72B need?
Qwen 72B requires 47.7 GB of VRAM at Q4_K_M, or 159.0 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 72.3B × 4.8 bits ÷ 8 = 43.4 GB
KV Cache + Overhead ≈ 4.3 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M47.7 GB- Can NVIDIA GeForce RTX 5090 run Qwen 72B?
No — Qwen 72B requires at least 32.8 GB at IQ3_XS, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for Qwen 72B?
For Qwen 72B, Q4_K_M (47.7 GB) offers the best balance of quality and VRAM usage. Q5_K_S (54.7 GB) provides better quality if you have the VRAM. The smallest option is IQ3_XS at 32.8 GB.
VRAM requirement by quantization
IQ3_XS32.8 GBIQ3_M35.8 GBIQ4_XS42.7 GBQ4_K_M ★47.7 GBQ5_K_M56.7 GBBF16159.0 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Qwen 72B on a Mac?
Qwen 72B requires at least 32.8 GB at IQ3_XS, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Qwen 72B locally?
Yes — Qwen 72B can run locally on consumer hardware. At Q4_K_M quantization it needs 47.7 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen 72B?
At Q4_K_M, Qwen 72B can reach ~101 tok/s on AMD Instinct MI350X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 47.7 × 0.65 = ~109 tok/s
Estimated speed at Q4_K_M (47.7 GB)
~109 tok/s~109 tok/s~101 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Qwen 72B?
At Q4_K_M, the download is about 43.37 GB. The full-precision BF16 version is 144.58 GB. The smallest option (IQ3_XS) is 29.82 GB.
- Which GPUs can run Qwen 72B?
No single consumer GPU has enough VRAM to run Qwen 72B at Q4_K_M (47.7 GB). Multi-GPU or professional hardware is required.
- Which devices can run Qwen 72B?
27 devices with unified memory can run Qwen 72B at Q4_K_M (47.7 GB), including ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.